Information Processing Structure Research Articles

生物規範型情報処理構造のロボット歩行制御に与える機能の実験的検証

Our purpose of research is to utilize the robot in open world as same as human live in. Living organisms have the capability of adapting their behaviors to unknown environmental situations. We consider that this capability consists of information processing structure and biological learning method. We have developed the robot motion controller with the information processing structure and biomimetic learning method and shown the function of proposed controller through the walking simulation studies. It has proposed that controller was able to create the adaptive walking to the environment, and adjusting a few parameters of the controller was able to create wide variety of walking, forward, backward and turning. In this paper, we experimentally verify that the proposed method can control the moving directions and emergence the balance of the humanoid robot according to the environmental situations.

Engineering coherent interactions in molecular nanomagnet dimers

AbstractProposals for systems embodying condensed matter spin qubits cover a very wide range of length scales, from atomic defects in semiconductors all the way to micron-sized lithographically defined structures. Intermediate scale molecular components exhibit advantages of both limits: like atomic defects, large numbers of identical components can be fabricated; as for lithographically defined structures, each component can be tailored to optimise properties such as quantum coherence. Here we demonstrate what is perhaps the most potent advantage of molecular spin qubits, the scalability of quantum information processing structures using bottom-up chemical self-assembly. Using Cr7Ni spin qubit building blocks, we have constructed several families of two-qubit molecular structures with a range of linking strategies. For each family, long coherence times are preserved, and we demonstrate control over the inter-qubit quantum interactions that can be used to mediate two-qubit quantum gates.

The Microstructure of Action Perception in Infancy: Decomposing the Temporal Structure of Social Information Processing.

In this article, we review recent evidence of infants' early competence in perceiving and interpreting the actions of others. We present a theoretical model that decomposes the timeline of action perception into a series of distinct processes that occur in a particular order. Once an agent is detected, covert attention can be allocated to the future state of the agent (priming), which may lead to overt gaze shifts that predict goals (prediction). Once these goals are achieved, the consequence of the agents' actions and the manner in which the actions were performed can be evaluated (evaluation). We propose that all of these processes have unique requirements, both in terms of timing and cognitive resources. To understand more fully the rich social world of infants, we need to pay more attention to the temporal structure of social perception and ask what information is available to infants and how this changes over time.

Basics for sensorimotor information processing: some implications for learning.

In sensorimotor activities, learning requires efficient information processing, whether in car driving, sport activities or human–machine interactions. Several factors may affect the efficiency of such processing: they may be extrinsic (i.e., task-related) or intrinsic (i.e., subjects-related). The effects of these factors are intimately related to the structure of human information processing. In the present article we will focus on some of them, which are poorly taken into account, even when minimizing errors or their consequences is an essential issue at stake. Among the extrinsic factors, we will discuss, first, the effects of the quantity and quality of information, secondly, the effects of instruction and thirdly motor program learning. Among the intrinsic factors, we will discuss first the influence of prior information, secondly how individual strategies affect performance and, thirdly, we will stress the fact that although the human brain is not structured to function errorless (which is not new) humans are able to detect their errors very quickly and (in most of the cases), fast enough to correct them before they result in an overt failure. Extrinsic and intrinsic factors are important to take into account for learning because (1) they strongly affect performance, either in terms of speed or accuracy, which facilitates or impairs learning, (2) the effect of certain extrinsic factors may be strongly modified by learning and (3) certain intrinsic factors might be exploited for learning strategies.

Information and decision-making delays in MRP, KANBAN, and CONWIP

A production control system (PCS) can be considered an information-processing organization (IPO). The performance of different production control systems has been studied intensively. However, their decision-making efficiency has not drawn much attention. The amount of information in a production control system can lead to a delay in decision-making. This paper considers the effect of product position information on decision-making. We use information entropy to measure the amount of position information in products and find that there are different amounts of position information in MRP, KANBAN, and CONWIP. Then, we compare the decision-making time delay among the three production control systems across identical organizational structures for information processing. We conclude that the production control system with the smallest amount of information spends the least amount of time in decision-making.

INFORMATION AND PREDICTABILITY: BOOKMAKERS, PREDICTION MARKETS AND TIPSTERS AS FORECASTERS

The more information is available, and the more predictable are events, the better forecasts ought to be. In this paper forecasts by bookmakers, prediction markets and tipsters are evaluated for a range of events with varying degrees of predictability and information availability. All three types of forecast represent different structures of information processing and as such would be expected to perform differently. By and large, events that are more predictable, and for which more information is available, do tend to be forecast better.

Systematic Approach to Computational Design of Gene Regulatory Networks with Information Processing Capabilities

We present several measures that can be used in de novo computational design of biological systems with information processing capabilities. Their main purpose is to objectively evaluate the behavior and identify the biological information processing structures with the best dynamical properties. They can be used to define constraints that allow one to simplify the design of more complex biological systems. These measures can be applied to existent computational design approaches in synthetic biology, i.e., rational and automatic design approaches. We demonstrate their use on a) the computational models of several basic information processing structures implemented with gene regulatory networks and b) on a modular design of a synchronous toggle switch.

Change one can believe in: Adding learning to computational models of self-regulation

Theories of self-regulation describe motivation as a dynamic process of goal choice and goal striving. To facilitate those processes, individuals learn about themselves and their environment, which is an internal dynamic process. However, the precise nature of the relationship between these learning and motivational processes is not well specified. This article integrates formal models of learning, goal choice, and goal striving using a single information processing structure found in self-regulatory models of motivation. Results from two published studies (DeShon & Rench, 2009; Schmidt & DeShon, 2007) validate the model. In both cases, the integrated model accounts for findings that previous theories of self-regulation could not explain. Discussion focuses on additional tests to validate the model and on the value of incorporating formal models from the cognitive, learning, and motivational literatures to account for behavior in complex settings and over time.

Remaining useful life prediction of grinding mill liners using an artificial neural network

Knowing the remaining useful life of grinding mill liners would greatly facilitate maintenance decisions. Now, a mill must be stopped periodically so that the maintenance engineer can enter, measure the liners’ wear, and make the appropriate maintenance decision. As mill stoppage leads to heavy production losses, the main aim of this study is to develop a method which predicts the remaining useful life of the liners, without needing to stop the mill. Because of the proven ability of artificial neural networks (ANNs) to recognize complex relationships between input and output variables, as well as its adaptive and parallel information-processing structure, an ANN has been designed based on the various process parameters which influence wear of the liners. The process parameters were considered as inputs while remaining height and remaining life of the liners were outputs. The results show remarkably high degree of correlation between the input and output variables. The performance of the neural network model is very consistent for data used for training (seen) and testing (unseen).

Co-oscillation and synchronization between the posterior thalamus and the caudate nucleus during visual stimulation

Recent results suggest significant cross-correlation between the spike trains of the suprageniculate nucleus (SG) of the posterior thalamus and the caudate nucleus (CN) during visual stimulation. In the present study visually evoked local field potentials (LFPs) were recorded simultaneously in the CN and the SG in order to investigate the coupling between these structures at a population level. The effect of static and dynamic visual stimulation was analyzed in 55 SG–CN LFP pairs in the frequency range 5–57Hz. Statistical analysis revealed significant correlation of the relative powers of each investigated frequency band (5–8Hz, 8–12Hz, 12–35Hz and 35–57Hz) during both static and dynamic visual stimulation. The temporal evolution of cross-correlation showed that in the majority of the cases the SG was activated first, and in approximately one third of the cases, the CN was activated earlier. These observations suggest a bidirectional information flow. The most interesting finding of this study is that different frequency bands exhibited significant cross-correlation in a stimulation paradigm-dependent manner. That is, static stimulation usually increased the cross-correlation of the higher frequency components (12–57Hz) of the LFP, while dynamic stimulation induced changes in the lowest frequency band (5–8Hz). This suggests a parallel processing of dynamic and static visual information in the SG and the CN. To our knowledge we are the first to provide evidence on the co-oscillation and synchronization of the CN and the SG at a population level upon visual stimulation, which suggests a significant cooperation between these structures in visual information processing.

Properties of intention: component structure and consequences for behavior, information processing, and resistance

AbstractThree studies tested the impact of properties of behavioral intention on intention–behavior consistency, information processing, and resistance. Principal components analysis showed that properties of intention formed distinct factors. Study 1 demonstrated that temporal stability, but not the other intention attributes, moderated intention–behavior consistency. Study 2 found that greater stability of intention was associated with improved memory performance. In Study 3, participants were confronted with a rating scale manipulation designed to alter their intention scores. Findings showed that stable intentions were able to withstand attack. Overall, the present research findings suggest that different properties of intention are not simply manifestations of a single underlying construct (“intention strength”), and that temporal stability exhibits superior resistance and impact compared to other intention attributes.

All-Optically Controlled Quantum Memory for Light with a Cavity-Optomechanical System

Optomechanics may be viewed as a light-mechanics interface to realize hybrid structures for (classical or quantum) information processing, switching or storage. Using the two-laser technique, in this paper, we theoretically devise a protocol for quantum light memory via a cavity optomechanical system composed of a Fabry–Perot cavity and a mechanical resonator. Due to the long-lived mechanical resonator, this quantum memory for light based on optomechanically induced transparency (OMIT) can serve as a long-term memory that can store the full quantum light contained in an optical pulse. It is shown that, with the tunable pump laser, the quantum signal light can be reaccelerated and converted back on demand. Our presented work could open the door to all-optical routers for light memory devices and have a guide to actual experiments.

Adaptive skeletal muscle action requires anticipation and "conscious broadcasting".

Historically, the conscious and anticipatory processes involved in voluntary action have been associated with the loftiest heights of nervous function. Concepts like mental time travel, “theory of mind,” and the formation of “the self” have been at the center of many attempts to determine the purpose of consciousness. Eventually, more reductionistic accounts of consciousness emerged, proposing rather that conscious states play a much more basic role in nervous function. Though the widely held integration consensus proposes that conscious states integrate information-processing structures and events that would otherwise be independent, Supramodular Interaction Theory (SIT) argues that conscious states are necessary for the integration of only certain kinds of information. As revealed in this selective review, this integration is related to what is casually referred to as “voluntary” action, which is intimately related to the skeletal muscle output system. Through a peculiar form of broadcasting, conscious integration often controls and guides action via “ideomotor” mechanisms, where anticipatory processes play a central role. Our selective review covers evidence (including findings from anesthesia research) for the integration consensus, SIT, and ideomotor theory.

Frames of reference and categorical and coordinate spatial relations: a hierarchical organisation

This research is about the role of categorical and coordinate spatial relations and allocentric and egocentric frames of reference in processing spatial information. To this end, we asked whether spatial information is firstly encoded with respect to a frame of reference or with respect to categorical/coordinate spatial relations. Participants had to judge whether two vertical bars appeared on the same side (categorical) or at the same distance (coordinate) with respect to the centre of a horizontal bar (allocentric) or with respect to their body midline (egocentric). The key manipulation was the timing of the instructions: one instruction (reference frame or spatial relation) was given before stimulus presentation, the other one after. If spatial processing requires egocentric/allocentric encoding before coordinate/categorical encoding, then spatial judgements should be facilitated when the frame of reference is specified in advance. In contrast, if categorical and coordinate dimensions are primary, then a facilitation should appear when the spatial relation is specified in advance. Results showed that participants were more accurate and faster when the reference frame rather than the type of spatial relation was provided before stimulus presentation. Furthermore, a selective facilitation was found for coordinate and categorical judgements after egocentric and allocentric cues, respectively. These results suggest a hierarchical structure of spatial information processing where reference frames play a primary role and selectively interact with subsequent processing of spatial relations.

Function Basis for Mechatronic System Design

A new function-oriented theoretical basis for mechatronic system design is presented in the paper, with a technology-independent functional description of such aspects in a mechatronic system as 1) relations and distinctions among purpose function, transformation function and state transition and 2) structure of information processing. All discussions are summarized in a set of principles, which consequently form the basis for devising design models and methods for mechatronic systems.

Full band structure calculation of two-photon indirect absorption in bulk silicon

Degenerate two-photon indirect absorption in silicon is an important limiting effect on the use of silicon structures for all-optical information processing at telecommunication wavelengths. We perform a full band structure calculation to investigate two-photon indirect absorption in bulk silicon, using a pseudopotential description of the energy bands and an adiabatic bond charge model to describe phonon dispersion and polarization. Our results agree well with some recent experimental results. The transverse acoustic/optical phonon-assisted processes dominate.

Social Work in the Laboratory: Using Microworlds for Practice Research

In cognitive ergonomics, laboratory experimentation using computer-based simulations (microworlds) has played a significant role in understanding human decision making and reasoning. In this paper, we describe the design and deployment of a social work microworld (BRIGIT), which simulates the electronic recording systems now widely implemented in UK children's services. BRIGIT provides a fabricated but realistic social work environment, enabling the fine structure of professional information processing to be studied in response to experimental manipulations, such as time pressure, etc. A preliminary experiment is described here, which shows BRIGIT to provide a convincing psychological experience and a useful research tool. As well as demonstrating its face and external validity, the results highlight BRIGIT's utility as a way of probing ‘practice culture’ and for examining different patterns of professional sense making. We conclude that the microworld paradigm provides a valuable and innovative approach for researching social work practice. A range of possible applications are discussed, not only in fundamental research, but as a practical tool for use in the workplace, such as for supporting staff selection. There is also obvious potential for ‘design research’ aimed directly at improving the usability and effectiveness of electronic systems, which is important given the widely reported problems of current ICT systems in social work.

Colored Motifs Reveal Computational Building Blocks in the C. elegans Brain

BackgroundComplex networks can often be decomposed into less complex sub-networks whose structures can give hints about the functional organization of the network as a whole. However, these structural motifs can only tell one part of the functional story because in this analysis each node and edge is treated on an equal footing. In real networks, two motifs that are topologically identical but whose nodes perform very different functions will play very different roles in the network.Methodology/Principal FindingsHere, we combine structural information derived from the topology of the neuronal network of the nematode C. elegans with information about the biological function of these nodes, thus coloring nodes by function. We discover that particular colorations of motifs are significantly more abundant in the worm brain than expected by chance, and have particular computational functions that emphasize the feed-forward structure of information processing in the network, while evading feedback loops. Interneurons are strongly over-represented among the common motifs, supporting the notion that these motifs process and transduce the information from the sensor neurons towards the muscles. Some of the most common motifs identified in the search for significant colored motifs play a crucial role in the system of neurons controlling the worm's locomotion.Conclusions/SignificanceThe analysis of complex networks in terms of colored motifs combines two independent data sets to generate insight about these networks that cannot be obtained with either data set alone. The method is general and should allow a decomposition of any complex networks into its functional (rather than topological) motifs as long as both wiring and functional information is available.

RESEARCH OF THE COMMUNICATION ABOUT INTERIOR FINISH WORK OF APARTMENT BUILDING

The interior finish work of apartment building is different of the length of job and the amount of work. This problem obstructs of homogenizing tact time because the progress of work is not equal. Moreover, the judgment by the worker and the foreman tends to become the best in the part. As the key which solves these problems, this paper takes notice of the architecture of the information of communication. First, it classifies the information processing structure of the construction team from the relation between the work flow and the information processing process. Next, it considers the point of the process control according to the team type from the relation between the role and the responsibility of the foreman and the worker. Last, this paper describes a problem on management about the construction system of the general contractor.

Information processing by biochemical networks: a dynamic approach

Understanding how information is encoded and transferred by biochemical networks is of fundamental importance in cellular and systems biology. This requires analysis of the relationships between the stochastic trajectories of the constituent molecular (or submolecular) species that comprise the network. We describe how to identify conditional independences between the trajectories or time courses of groups of species. These are robust network properties that provide important insight into how information is processed. An entire network can then be decomposed exactly into modules on informational grounds. In the context of signalling networks with multiple inputs, the approach identifies the routes and species involved in sequential information processing between input and output modules. An algorithm is developed which allows automated identification of decompositions for large networks and visualization using a tree that encodes the conditional independences. Only stoichiometric information is used and neither simulations nor knowledge of rate parameters are required. A bespoke version of the algorithm for signalling networks identifies the routes of sequential encoding between inputs and outputs, visualized as paths in the tree. Application to the toll-like receptor signalling network reveals that inputs can be informative in ways unanticipated by steady-state analyses, that the information processing structure is not well described as a bow tie, and that encoding for the interferon response is unusually sparse compared with other outputs of this innate immune system.